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copied!<p>Message Passing Interface (MPI) (<a href="http://www-unix.mcs.anl.gov/mpi/" rel="noreferrer">http://www-unix.mcs.anl.gov/mpi/</a>) is a highly scalable and robust library for parallel programming, geared original towards C but now available in several flavors <a href="http://en.wikipedia.org/wiki/Message_Passing_Interface#Implementations" rel="noreferrer">http://en.wikipedia.org/wiki/Message_Passing_Interface#Implementations</a>. While the library doesn't introduce new syntax, it provides a communication protocol to orchestrate the sharing of data between routines which are parallelizable.</p> <p>Traditionally, it is used in large cluster computing rather than on a single system for concurrency, although multi-core systems can certainly take advantage of this library.</p> <p>Another interesting solution to the problem of parallel programming is OpenMP, which is an attempt to provide a portable extension on various platforms to provide hints to the compiler about what sections of code are easily parallelizable.</p> <p>For example (<a href="http://en.wikipedia.org/wiki/OpenMP#Work-sharing_constructs" rel="noreferrer">http://en.wikipedia.org/wiki/OpenMP#Work-sharing_constructs</a>):</p> <pre><code>#define N 100000 int main(int argc, char *argv[]) { int i, a[N]; #pragma omp parallel for for (i=0;i<N;i++) a[i]= 2*i; return 0; } </code></pre> <p>There are advantages and disadvantages to both, of course, but the former has proven to be extremely successful in academia and other heavy scientific computing applications. YMMV.</p>

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